The application of regional factors in the extraction of Remote Sensing information
Chen Minzhen
Lab. of Agricultural Remote Sensing
Zhejiang Agricultural University
Zhao Yuanhong, Chen Lan, He Kan
Lab. of Remote Sensing University,
Zhejiang Remote Sensing Centre
China
Abstract
This paper selects Junshan Hill Area, which lies between Dongting Lake and Yangtze River, as an experimental area, and a TM image (flood season) as experimental data. On the basic of studying spectral features and distribution patterns of various surface target, the experimental area is divided into three types: the field inside embankments, the transitional field outside embankments, and the water field. Some types of surface target, which have identical or similar spectral features but lie in different regional factors, can be distinguished according to regional factors. Other surface target which have different spectral features but lie in the same regions, can be distinguished by making use f threshold extraction method. Several different type of field are successfully distinguished in this way, they are the reed field, the reed weed field, the mud sand river water containing high mud sand content, lake water containing mid mud-sand content, the low mud-sand content water inside embankments, and the flooded area. The research indicates that it is feasible and effective to introduce regional factors into the extraction of RS thematic information. The approach is conducive to the efficient monitoring of flood.
Introduction
The application of remote sensing information greatly depends on the efficient extraction of various thematic information. Nowadays, computer automatic extraction (classification) has became the mainstream of research on information extraction techniques. Because of the restriction of spectral and spatial resolution in RS information, researchers introduce some other sources of information in order to extract RS thematic information greatly. This paper presents and approach of how to extract various types of water information efficiently and accurately from RS images, and discusses a general method of how to introduce some regional factors into the extraction of RS thematic information according tot eh distribution patterns of natural surface target. Junshan hill farm is selected as a experimental area which is lies between Yangtze River and Dongting Lake. A TM image (Aug. 25 1987 flood season) is used as the experimental data.
